code: def initialise_selective_sampler(self):
      # print("Initialisation ",
      #       self.segmentation_param.compulsory_labels,
      #       self.segmentation_param.proba_connect)
      # print(self.segmentation_param.num_min_labels,
      #       self.segmentation_param.proba_connect)
      selective_constraints = Constraint(
          self.segmentation_param.compulsory_labels,
          self.segmentation_param.min_sampling_ratio,
          self.segmentation_param.min_numb_labels,
          self.segmentation_param.proba_connect,
      )
      self.sampler = [
          [
              SelectiveSampler(
                  reader=reader,
                  data_param=self.data_param,
                  batch_size=self.net_param.batch_size,
                  windows_per_image=self.action_param.sample_per_volume,
                  constraint=selective_constraints,
                  random_windows_per_image=self.segmentation_param.rand_samples,
                  queue_length=self.net_param.queue_length,
              )
              for reader in self.readers
          ]
      ]
  
imports: import tensorflow
  from niftynet.application.base_application import BaseApplication
  from niftynet.contrib.segmentation_selective_sampler.sampler_selective import SelectiveSampler, Constraint
  from niftynet.engine.application_factory import ApplicationNetFactory, InitializerFactory, OptimiserFactory
  from niftynet.engine.application_variables import CONSOLE, NETWORK_OUTPUT, TF_SUMMARIES
  from niftynet.engine.sampler_grid_v2 import GridSampler
  from niftynet.engine.windows_aggregator_grid import GridSamplesAggregator
  from niftynet.io.image_reader import ImageReader
  from niftynet.layer.binary_masking import BinaryMaskingLayer
  from niftynet.layer.discrete_label_normalisation import DiscreteLabelNormalisationLayer
  from niftynet.layer.histogram_normalisation import HistogramNormalisationLayer
  from niftynet.layer.loss_segmentation import LossFunction
  from niftynet.layer.mean_variance_normalisation import MeanVarNormalisationLayer
  from niftynet.layer.pad import PadLayer
  from niftynet.layer.post_processing import PostProcessingLayer
  from niftynet.layer.rand_flip import RandomFlipLayer
  from niftynet.layer.rand_rotation import RandomRotationLayer
  from niftynet.layer.rand_spatial_scaling import RandomSpatialScalingLayer
label_desc: Use image node_id 3 for calling the SelectiveSampling obj's underlying member method code with example usage: obj.initialise_selective_sampler() without return types